rm(list = ls())
set.seed(2024)
library(tidyverse)
library(here)
library(phyloseq)
library(vegan)
library(rstatix)
theme_set(theme_bw())
max.core <- parallel::detectCores()
ps.rare <- readRDS(here('data','following_study','ps_rarefied.rds'))
sample_data(ps.rare)$Shannon <- estimate_richness(ps.rare)$Shannon
# transform data into proportion
ps.rare.prop <- ps.rare %>%
transform_sample_counts(function(x) x/sum(x))
sam <- data.frame(sample_data(ps.rare.prop))
plot_ord draws ordination plot for different factors
using plot_ordination function in phyloseq
package.
permanova performs permutational multivariate analysis
of variance (PERMANOVA) based on adonis2 function in
vegan package.
permdisp performs permutational analysis of multivariate
dispersions (PERMDISP) based on betadisper function in
vegan package.
plot_ord <- function(data, factor, method, distance){
data.ord <- ordinate(data, method = method, distance = distance)
p <- plot_ordination(data, data.ord, color = factor)
p <- p + stat_ellipse(type = "t",geom = "polygon",alpha = 0)
p <- p + ggtitle(str_c(factor,method,distance, sep = ' - '))
print(p)
}
permanova <- function(data, formula, method, permutations=1e4, strata = NULL, core = max.core){
message('PERMANOVA Model: ', method, '~', formula, '; Strata: ', ifelse(is_null(strata), 'None', as.character(strata)))
dist.matrix <- phyloseq::distance(data, method=method)
df <- data.frame(sample_data(data))
model <- as.formula(paste0('dist.matrix~', formula))
if (!is_null(strata)) {strata <- df[,strata]}
result <- adonis2(model,
data = df,
permutations=permutations,
strata = strata,
parallel = core,
by = 'term',
na.action = na.omit)
return(result)
}
permdisp <- function(data, group, method, permutations=1e4, pairwise = FALSE, core = max.core){
message('PERMDISP Model: ', method, '~', group)
dist.matrix <- phyloseq::distance(data, method=method)
df <- data.frame(sample_data(data))
beta.disp <- betadisper(dist.matrix, group = df[,group])
result <- permutest(beta.disp, permutations = permutations, pairwise = pairwise, type = 'centroid')
return(result)
}
In this section, we want to estimate the effect of different factors
on dog microbiomes. We focused on Household,
Epileptic.or.Control, Breed.Group..1.,
Pheno.Y.N, Sex, and
Age..months..
We compare the alpha diversity (Shannon index) among different factors using ANOVA.
We compare the beta diversity of different factors using PERMANOVA using the Bray-Curtis and weighted Unifrac distance, and visualized using multi-dimensional scaling.
PERMDISP was used to test the homogeneity of multivariate dispersions among groups.
ggplot(sam,aes(x = as.numeric(Household), y = Shannon, group = Household)) +
geom_point() + geom_line() + xlab('Household')
anova_test(Shannon~Household, data = sam, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Household 48 49 1.599 0.053 0.61
Here we see the Shannon diversity index is significantly different among households.
permanova(ps.rare.prop, 'Household', 'bray')
## PERMANOVA Model: bray~Household; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 12.2248 0.6893 2.2647 9.999e-05 ***
## Residual 49 5.5104 0.3107
## Total 97 17.7352 1.0000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permanova(ps.rare.prop, 'Household', 'wunifrac')
## PERMANOVA Model: wunifrac~Household; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 1.90306 0.67767 2.1462 9.999e-05 ***
## Residual 49 0.90517 0.32233
## Total 97 2.80823 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
ggplot(sam, aes(x = Epileptic.or.Control, y = Shannon)) +
geom_boxplot() + geom_jitter(height = 0, width = 0.25)
anova_test(Shannon~Household+Epileptic.or.Control, data = sam, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Household 48 48 1.568 0.061 0.611
## 2 Epileptic.or.Control 1 48 0.067 0.796 0.001
plot_ord(ps.rare.prop, 'Epileptic.or.Control','MDS','bray')
plot_ord(ps.rare.prop, 'Epileptic.or.Control','NMDS','bray')
## Run 0 stress 0.2089049
## Run 1 stress 0.2200629
## Run 2 stress 0.2215701
## Run 3 stress 0.2191062
## Run 4 stress 0.2105267
## Run 5 stress 0.233624
## Run 6 stress 0.2301806
## Run 7 stress 0.2046962
## ... New best solution
## ... Procrustes: rmse 0.02758093 max resid 0.2550759
## Run 8 stress 0.2225389
## Run 9 stress 0.2040715
## ... New best solution
## ... Procrustes: rmse 0.03769366 max resid 0.3007093
## Run 10 stress 0.2213932
## Run 11 stress 0.2217022
## Run 12 stress 0.2115462
## Run 13 stress 0.2106959
## Run 14 stress 0.2097634
## Run 15 stress 0.2042154
## ... Procrustes: rmse 0.03712412 max resid 0.2768694
## Run 16 stress 0.2087932
## Run 17 stress 0.2212572
## Run 18 stress 0.2053057
## Run 19 stress 0.204233
## ... Procrustes: rmse 0.03415718 max resid 0.3155705
## Run 20 stress 0.2206824
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 5: no. of iterations >= maxit
## 15: stress ratio > sratmax
permanova(ps.rare.prop, 'Epileptic.or.Control', 'bray', strata = 'Household')
## PERMANOVA Model: bray~Epileptic.or.Control; Strata: Household
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Blocks: strata
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Epileptic.or.Control 1 0.1584 0.00893 0.8651 0.09049 .
## Residual 96 17.5768 0.99107
## Total 97 17.7352 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.rare.prop, 'Epileptic.or.Control', 'bray')
## PERMDISP Model: bray~Epileptic.or.Control
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.00182 0.0018249 0.1221 10000 0.7335
## Residuals 96 1.43422 0.0149398
plot_ord(ps.rare.prop, 'Epileptic.or.Control','MDS','wunifrac')
plot_ord(ps.rare.prop, 'Epileptic.or.Control','NMDS','wunifrac')
## Run 0 stress 0.1677058
## Run 1 stress 0.1773885
## Run 2 stress 0.1662523
## ... New best solution
## ... Procrustes: rmse 0.04596998 max resid 0.1482302
## Run 3 stress 0.167717
## Run 4 stress 0.1658647
## ... New best solution
## ... Procrustes: rmse 0.0622066 max resid 0.358157
## Run 5 stress 0.1708145
## Run 6 stress 0.1699045
## Run 7 stress 0.1703389
## Run 8 stress 0.1638635
## ... New best solution
## ... Procrustes: rmse 0.01674709 max resid 0.1152441
## Run 9 stress 0.1765167
## Run 10 stress 0.171215
## Run 11 stress 0.1739947
## Run 12 stress 0.1712411
## Run 13 stress 0.1734899
## Run 14 stress 0.171567
## Run 15 stress 0.1691978
## Run 16 stress 0.1660252
## Run 17 stress 0.1706175
## Run 18 stress 0.1727989
## Run 19 stress 0.1740083
## Run 20 stress 0.1685239
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 2: no. of iterations >= maxit
## 18: stress ratio > sratmax
permanova(ps.rare.prop, 'Epileptic.or.Control', 'wunifrac', strata = 'Household')
## PERMANOVA Model: wunifrac~Epileptic.or.Control; Strata: Household
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Blocks: strata
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Epileptic.or.Control 1 0.04037 0.01437 1.4001 0.0423 *
## Residual 96 2.76786 0.98563
## Total 97 2.80823 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.rare.prop, 'Epileptic.or.Control', 'wunifrac')
## PERMDISP Model: wunifrac~Epileptic.or.Control
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.00698 0.0069804 1.867 10000 0.1746
## Residuals 96 0.35893 0.0037389
ps.breed <- ps.rare.prop %>%
subset_samples(!is.na(Breed.Group..1.) & is.na(Breed.Group..2.))
ps.breed
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 2548 taxa and 76 samples ]
## sample_data() Sample Data: [ 76 samples by 29 sample variables ]
## tax_table() Taxonomy Table: [ 2548 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 2548 tips and 2547 internal nodes ]
## refseq() DNAStringSet: [ 2548 reference sequences ]
sam.breed <- data.frame(sample_data(ps.breed))
ggplot(sam.breed) +
geom_point(aes(x = Breed.Group..1., y = Shannon, colour = Breed.Group..1.)) +
theme(axis.text.x = element_blank(), axis.ticks.x.bottom = element_blank())
anova_test(Shannon~Household + Breed.Group..1., data = sam.breed, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Household 40 30 1.667 0.074 0.690
## 2 Breed.Group..1. 5 30 0.505 0.770 0.078
plot_ord(ps.breed, 'Breed.Group..1.','MDS','bray')
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
plot_ord(ps.breed, 'Breed.Group..1.','NMDS','bray')
## Run 0 stress 0.2032089
## Run 1 stress 0.2056965
## Run 2 stress 0.2043175
## Run 3 stress 0.2132212
## Run 4 stress 0.2147094
## Run 5 stress 0.2136878
## Run 6 stress 0.2050429
## Run 7 stress 0.2026264
## ... New best solution
## ... Procrustes: rmse 0.03578144 max resid 0.1609715
## Run 8 stress 0.20483
## Run 9 stress 0.2126997
## Run 10 stress 0.2145529
## Run 11 stress 0.2320328
## Run 12 stress 0.2054623
## Run 13 stress 0.2026752
## ... Procrustes: rmse 0.02116857 max resid 0.1156994
## Run 14 stress 0.2009081
## ... New best solution
## ... Procrustes: rmse 0.06633316 max resid 0.2316631
## Run 15 stress 0.1982802
## ... New best solution
## ... Procrustes: rmse 0.04418728 max resid 0.2539096
## Run 16 stress 0.2010472
## Run 17 stress 0.1984365
## ... Procrustes: rmse 0.03302231 max resid 0.1413722
## Run 18 stress 0.2212248
## Run 19 stress 0.1983042
## ... Procrustes: rmse 0.03150234 max resid 0.1524821
## Run 20 stress 0.1979161
## ... New best solution
## ... Procrustes: rmse 0.01354783 max resid 0.07492009
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 4: no. of iterations >= maxit
## 16: stress ratio > sratmax
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
permanova(ps.breed, 'Household + Breed.Group..1.', 'bray')
## PERMANOVA Model: bray~Household + Breed.Group..1.; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 40 9.6517 0.71619 2.291 9.999e-05 ***
## Breed.Group..1. 5 0.6651 0.04935 1.263 0.1432
## Residual 30 3.1596 0.23445
## Total 75 13.4763 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.breed, 'Breed.Group..1.', 'bray')
## PERMDISP Model: bray~Breed.Group..1.
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 6 0.0692 0.011534 0.7323 10000 0.6191
## Residuals 69 1.0868 0.015751
plot_ord(ps.breed, 'Breed.Group..1.','MDS','wunifrac')
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
plot_ord(ps.breed, 'Breed.Group..1.','NMDS','wunifrac')
## Run 0 stress 0.1708208
## Run 1 stress 0.1655651
## ... New best solution
## ... Procrustes: rmse 0.06717692 max resid 0.259309
## Run 2 stress 0.1695212
## Run 3 stress 0.1653788
## ... New best solution
## ... Procrustes: rmse 0.01218192 max resid 0.07788304
## Run 4 stress 0.1803572
## Run 5 stress 0.1690298
## Run 6 stress 0.1667782
## Run 7 stress 0.1643756
## ... New best solution
## ... Procrustes: rmse 0.02868352 max resid 0.1110408
## Run 8 stress 0.1641162
## ... New best solution
## ... Procrustes: rmse 0.06546367 max resid 0.2741744
## Run 9 stress 0.1694481
## Run 10 stress 0.1664819
## Run 11 stress 0.169577
## Run 12 stress 0.163923
## ... New best solution
## ... Procrustes: rmse 0.03862454 max resid 0.176506
## Run 13 stress 0.1669618
## Run 14 stress 0.1619331
## ... New best solution
## ... Procrustes: rmse 0.03175062 max resid 0.1756096
## Run 15 stress 0.1681841
## Run 16 stress 0.1694186
## Run 17 stress 0.162219
## ... Procrustes: rmse 0.00912344 max resid 0.06310805
## Run 18 stress 0.1659121
## Run 19 stress 0.1671885
## Run 20 stress 0.1621137
## ... Procrustes: rmse 0.007986208 max resid 0.06120646
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 20: stress ratio > sratmax
## Too few points to calculate an ellipse
## Too few points to calculate an ellipse
permanova(ps.breed, 'Household + Breed.Group..1.', 'wunifrac')
## PERMANOVA Model: wunifrac~Household + Breed.Group..1.; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 40 1.52201 0.71072 2.3032 9.999e-05 ***
## Breed.Group..1. 5 0.12387 0.05784 1.4995 0.1014
## Residual 30 0.49562 0.23144
## Total 75 2.14150 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.breed, 'Breed.Group..1.', 'wunifrac')
## PERMDISP Model: wunifrac~Breed.Group..1.
## Warning in betadisper(dist.matrix, group = df[, group]): some squared distances
## are negative and changed to zero
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 6 0.00548 0.0009135 0.1974 10000 0.9796
## Residuals 69 0.31932 0.0046278
ps.drug <- ps.rare.prop %>%
subset_samples(Epileptic.or.Control == 'Epileptic')
sam.drug <- data.frame(sample_data(ps.drug))
ggplot(sam.drug, aes(x = Pheno.Y.N, y = Shannon)) +
geom_boxplot() + geom_jitter(height = 0, width = 0.25)
anova_test(Shannon~Pheno.Y.N, data = sam.drug, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Pheno.Y.N 1 47 0.917 0.343 0.019
plot_ord(ps.drug, 'Pheno.Y.N','MDS','bray')
plot_ord(ps.drug, 'Pheno.Y.N','NMDS','bray')
## Run 0 stress 0.2019485
## Run 1 stress 0.2182105
## Run 2 stress 0.2045303
## Run 3 stress 0.2193361
## Run 4 stress 0.204727
## Run 5 stress 0.2026006
## Run 6 stress 0.2282813
## Run 7 stress 0.2027367
## Run 8 stress 0.2164618
## Run 9 stress 0.2303987
## Run 10 stress 0.2059
## Run 11 stress 0.2114223
## Run 12 stress 0.2068373
## Run 13 stress 0.2052279
## Run 14 stress 0.2191267
## Run 15 stress 0.2074245
## Run 16 stress 0.2082746
## Run 17 stress 0.2246078
## Run 18 stress 0.2074868
## Run 19 stress 0.212465
## Run 20 stress 0.2082626
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 3: no. of iterations >= maxit
## 17: stress ratio > sratmax
permanova(ps.drug, 'Pheno.Y.N', 'bray')
## PERMANOVA Model: bray~Pheno.Y.N; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Pheno.Y.N 1 0.1776 0.02081 0.9991 0.4374
## Residual 47 8.3565 0.97919
## Total 48 8.5341 1.00000
permdisp(ps.drug, 'Pheno.Y.N', 'bray')
## PERMDISP Model: bray~Pheno.Y.N
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.01559 0.015594 1.181 10000 0.2784
## Residuals 47 0.62059 0.013204
plot_ord(ps.drug, 'Pheno.Y.N','MDS','wunifrac')
plot_ord(ps.drug, 'Pheno.Y.N','NMDS','wunifrac')
## Run 0 stress 0.1787197
## Run 1 stress 0.1912654
## Run 2 stress 0.1974609
## Run 3 stress 0.1909486
## Run 4 stress 0.1973358
## Run 5 stress 0.1843501
## Run 6 stress 0.1811664
## Run 7 stress 0.4021801
## Run 8 stress 0.1905269
## Run 9 stress 0.1960564
## Run 10 stress 0.1795665
## Run 11 stress 0.1838092
## Run 12 stress 0.1829075
## Run 13 stress 0.185102
## Run 14 stress 0.1821448
## Run 15 stress 0.190412
## Run 16 stress 0.1885809
## Run 17 stress 0.1822979
## Run 18 stress 0.1875528
## Run 19 stress 0.1902957
## Run 20 stress 0.1821812
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 20: stress ratio > sratmax
permanova(ps.drug, 'Pheno.Y.N', 'wunifrac')
## PERMANOVA Model: wunifrac~Pheno.Y.N; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Pheno.Y.N 1 0.01755 0.01429 0.6816 0.7432
## Residual 47 1.21039 0.98571
## Total 48 1.22794 1.00000
permdisp(ps.drug, 'Pheno.Y.N', 'wunifrac')
## PERMDISP Model: wunifrac~Pheno.Y.N
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.008442 0.0084418 2.7053 10000 0.1051
## Residuals 47 0.146663 0.0031205
prop.test(xtabs(~Household+Sex, data = sam))
## Warning in prop.test(xtabs(~Household + Sex, data = sam)): Chi-squared
## approximation may be incorrect
##
## 49-sample test for equality of proportions without continuity
## correction
##
## data: xtabs(~Household + Sex, data = sam)
## X-squared = 52.464, df = 48, p-value = 0.3051
## alternative hypothesis: two.sided
## sample estimates:
## prop 1 prop 2 prop 3 prop 4 prop 5 prop 6 prop 7 prop 8 prop 9 prop 10
## 0.5 0.5 0.0 1.0 0.0 1.0 1.0 0.5 1.0 1.0
## prop 11 prop 12 prop 13 prop 14 prop 15 prop 16 prop 17 prop 18 prop 19 prop 20
## 0.5 1.0 1.0 1.0 0.5 0.5 1.0 1.0 0.0 0.5
## prop 21 prop 22 prop 23 prop 24 prop 25 prop 26 prop 27 prop 28 prop 29 prop 30
## 0.0 0.5 1.0 0.5 0.5 0.0 0.0 0.0 0.5 0.5
## prop 31 prop 32 prop 33 prop 34 prop 35 prop 36 prop 37 prop 38 prop 39 prop 40
## 1.0 0.5 1.0 1.0 0.0 0.5 0.5 0.5 0.5 0.5
## prop 41 prop 42 prop 43 prop 44 prop 45 prop 46 prop 47 prop 48 prop 49
## 0.0 1.0 1.0 0.5 0.5 1.0 0.5 1.0 0.5
ggplot(sam, aes(x = Sex, y = Shannon)) +
geom_boxplot() + geom_jitter(height = 0, width = 0.25)
anova_test(Shannon~Household+Sex, data = sam, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Household 48 48 1.634 0.046 * 0.620
## 2 Sex 1 48 2.085 0.155 0.042
plot_ord(ps.rare.prop, 'Sex','MDS','bray')
plot_ord(ps.rare.prop, 'Sex','NMDS','bray')
## Run 0 stress 0.2089049
## Run 1 stress 0.2230145
## Run 2 stress 0.2313955
## Run 3 stress 0.2047349
## ... New best solution
## ... Procrustes: rmse 0.02793474 max resid 0.2557777
## Run 4 stress 0.2042607
## ... New best solution
## ... Procrustes: rmse 0.04853521 max resid 0.4174251
## Run 5 stress 0.2046638
## ... Procrustes: rmse 0.006529649 max resid 0.05485916
## Run 6 stress 0.2246074
## Run 7 stress 0.2093822
## Run 8 stress 0.2104461
## Run 9 stress 0.2028582
## ... New best solution
## ... Procrustes: rmse 0.04015983 max resid 0.3241834
## Run 10 stress 0.2040942
## Run 11 stress 0.2088666
## Run 12 stress 0.2040468
## Run 13 stress 0.2042522
## Run 14 stress 0.2093865
## Run 15 stress 0.2049003
## Run 16 stress 0.2037889
## Run 17 stress 0.2038654
## Run 18 stress 0.2031013
## ... Procrustes: rmse 0.005698808 max resid 0.04047538
## Run 19 stress 0.2042237
## Run 20 stress 0.2037019
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 4: no. of iterations >= maxit
## 16: stress ratio > sratmax
permanova(ps.rare.prop, 'Household+Sex', 'bray')
## PERMANOVA Model: bray~Household+Sex; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 12.2248 0.68930 2.2419 9.999e-05 ***
## Sex 1 0.0575 0.00324 0.5062 0.9813
## Residual 48 5.4529 0.30746
## Total 97 17.7352 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.rare.prop, 'Sex', 'bray')
## PERMDISP Model: bray~Sex
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.01776 0.017760 1.2052 10000 0.2726
## Residuals 96 1.41464 0.014736
plot_ord(ps.rare.prop, 'Sex','MDS','wunifrac')
plot_ord(ps.rare.prop, 'Sex','NMDS','wunifrac')
## Run 0 stress 0.1677058
## Run 1 stress 0.1688282
## Run 2 stress 0.1763593
## Run 3 stress 0.1753479
## Run 4 stress 0.1676147
## ... New best solution
## ... Procrustes: rmse 0.02692823 max resid 0.1579898
## Run 5 stress 0.1766771
## Run 6 stress 0.1659421
## ... New best solution
## ... Procrustes: rmse 0.06233402 max resid 0.3920605
## Run 7 stress 0.1737135
## Run 8 stress 0.1665561
## Run 9 stress 0.1703588
## Run 10 stress 0.169404
## Run 11 stress 0.1710069
## Run 12 stress 0.1688368
## Run 13 stress 0.166964
## Run 14 stress 0.1672809
## Run 15 stress 0.1663042
## ... Procrustes: rmse 0.05890682 max resid 0.3666806
## Run 16 stress 0.1706029
## Run 17 stress 0.175832
## Run 18 stress 0.1670706
## Run 19 stress 0.1734538
## Run 20 stress 0.1661993
## ... Procrustes: rmse 0.03242898 max resid 0.2115321
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 2: no. of iterations >= maxit
## 18: stress ratio > sratmax
permanova(ps.rare.prop, 'Household+Sex', 'wunifrac')
## PERMANOVA Model: wunifrac~Household+Sex; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 1.90306 0.67767 2.1118 9.999e-05 ***
## Sex 1 0.00402 0.00143 0.2139 0.9966
## Residual 48 0.90115 0.32090
## Total 97 2.80823 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permdisp(ps.rare.prop, 'Sex', 'wunifrac')
## PERMDISP Model: wunifrac~Sex
##
## Permutation test for homogeneity of multivariate dispersions
## Permutation: free
## Number of permutations: 10000
##
## Response: Distances
## Df Sum Sq Mean Sq F N.Perm Pr(>F)
## Groups 1 0.00158 0.0015789 0.3971 10000 0.5401
## Residuals 96 0.38166 0.0039757
age <- sam %>%
group_by(Household) %>%
summarise(age.diff = abs(diff(Age..months./12)))
age$age.diff %>% hist()
age$age.diff %>% summary()
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 2.000 2.963 5.000 10.000
sum(age$age.diff < 4.5)
## [1] 35
ggplot(sam) +
geom_line(aes(x = as.numeric(Household), y = Age..months., group = Household)) +
geom_point(aes(x = as.numeric(Household), y = Age..months., group = Household, colour = Epileptic.or.Control)) +
xlab('Household') + ylab('Age in month')
anova_test(Shannon~Household+Age..months., data = sam, type = 1)
## ANOVA Table (type I tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Household 48 48 1.566 0.062 0.610000
## 2 Age..months. 1 48 0.010 0.920 0.000215
permanova(ps.rare.prop, 'Household + Age..months.', 'bray')
## PERMANOVA Model: bray~Household + Age..months.; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 12.2248 0.68930 2.2618 9.999e-05 ***
## Age..months. 1 0.1056 0.00595 0.9377 0.5228
## Residual 48 5.4048 0.30475
## Total 97 17.7352 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
permanova(ps.rare.prop, 'Household + Age..months.', 'wunifrac')
## PERMANOVA Model: wunifrac~Household + Age..months.; Strata: None
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 10000
##
## adonis2(formula = model, data = df, permutations = permutations, by = "term", parallel = core, na.action = na.omit, strata = strata)
## Df SumOfSqs R2 F Pr(>F)
## Household 48 1.90306 0.67767 2.1420 9.999e-05 ***
## Age..months. 1 0.01672 0.00596 0.9036 0.4899
## Residual 48 0.88844 0.31637
## Total 97 2.80823 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
sessioninfo::session_info()
## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.4.1 (2024-06-14)
## os macOS 15.5
## system aarch64, darwin20
## ui X11
## language (EN)
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## ctype en_US.UTF-8
## tz America/New_York
## date 2025-06-13
## pandoc 3.5 @ /Users/yixuanyang/miniforge3/bin/ (via rmarkdown)
##
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